Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer

OBJECTIVES: To develop and validate a multiparametric model to predict neoadjuvant treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI dataset. METHODS: Baseline staging MRIs (T2W (T2-weighted)-MRI, diffusion-weighted imaging (DWI) / apparent diffusion coefficient (...

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Detalles Bibliográficos
Autores principales: Schurink, Niels W., van Kranen, Simon R., van Griethuysen, Joost J. M., Roberti, Sander, Snaebjornsson, Petur, Bakers, Frans C. H., de Bie, Shira H., Bosma, Gerlof P. T., Cappendijk, Vincent C., Geenen, Remy W. F., Neijenhuis, Peter A., Peterson, Gerald M., Veeken, Cornelis J., Vliegen, Roy F. A., Peters, Femke P., Bogveradze, Nino, el Khababi, Najim, Lahaye, Max J., Maas, Monique, Beets, Geerard L., Beets-Tan, Regina G. H., Lambregts, Doenja M. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667134/
https://www.ncbi.nlm.nih.gov/pubmed/37452176
http://dx.doi.org/10.1007/s00330-023-09920-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667134/
https://www.ncbi.nlm.nih.gov/pubmed/37452176
http://dx.doi.org/10.1007/s00330-023-09920-6

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